How to Use AI in Automation Testing??

AI in automation testing enhances efficiency, accuracy, and test maintenance by leveraging machine learning and intelligent algorithms. It enables self-healing test scripts, reducing manual intervention when UI elements change. AI-driven test case generation identifies high-risk areas, optimizing coverage and ensuring robust software validation.

AI improves defect detection by analyzing application behavior, predicting failures, and identifying anomalies that traditional automation may overlook. It also enhances visual testing, ensuring UI consistency across different devices and screen resolutions. By integrating AI into automation testing, organizations can accelerate release cycles, minimize test maintenance efforts, and improve overall software quality with greater precision and reliability.